Extracting Linguistic Knowledge from an International Classification

Automatic extraction of knowledge from large corpus of texts is an essential step toward linguistic knowledge acquisition in the medical domain. The current situation shows a lack of computer-readable large medical lexicons, with a partial exception for the English language. Moreover, multilingual lexicons with versatility for multiple languages applications are far from reach as long as only manual extraction is considered. Computer-assisted linguistic knowledge acquisition is a must. A multilingual lexicon differs from a monolingual one by the necessity to bridge the words in different languages. A kind of interlingua has to be built under the form of concepts to which the specific entries are attached. In the present approach, the authors have developed an intelligent rule-based tool in order to focus on a multilingual source of medical knowledge like the International Classification of Disease (ICD) which contains a vocabulary of some 20'000 words, translated in numerous languages.